
*This is the replication Stata do-file for Berkay, Alica and Schakel, Arjan H. (2025) 'Does multilevel government increase legitimacy? Citizens' preferences for subnational authority and acceptance of governmental decisions,' Journal of Public Policy, forthcoming. 

*Open dataset: Alica_Schakel_2025_JPP_replication_dataset.dta
{The following changes have been implemented to prepare the dataset produced by R for use in Stata.

encode(responseid), gen(id)

*tier is a recoded variable that traces the decision_maker: 1=N; 2=C; 3=M.
*treatment_nr is a recoded variable that traces the 'support treatment': 1=C; 2=C+N; 3=M; 4=M+C; 5=M+N; 6=N.
}


{Table 2. Survey items used to tap preferences for subnational authority.

factor sf1 sf2 sf3 sh1 sh2 sh3 if tier==1, pcf

alpha sf1 sf2 sf3 sh1 sh2 sh3 if tier==1
}

{Figure 2. Share of respondents who are (not) willing to accept a decision.

by tier, sort : tabulate first_answer_original
}

{Figure 3. The impact of preferences for subnational authority on the willingness to accept a decision taken by a municipality, county, or the national government.

*IMPORTANT NOTE: The point estimates are different from those produced by R and shown in Figure 3 in the main text. This is because Stata and R take different (respondent) base categories. The differences between the point estimates are the same and lead to the same findings.

*The point estimates are statistically significantly different from each other at p<0.05 when their 84% CIs do not overlap and at p<0.01 when their 95% CIs do not overlap (Greenland et al. 2016; Julius 2004; Macgregor-Fors and Payton 2013). R and Stata produce slightly different CIs whereby estimates are different at the second (hundreths) or third (thousands) digit behind the decimal point. In some instances, this leads to some discrepancies between R and Stata in assigning statistical significance. In all cases of discrepancies, the R estimates are more conservative, i.e. R indicates non-significance and p<0.05 whereas Stata indicates respectively p<0.05 and p<0.01. The statistical significance levels shown in the Figures in the main text and in the Supplementary Materials are based on the more conservative R estimates. 

xtset id tier

xtreg first_answer ib(1).tier##c.psa, fe cluster(id)

margins, at( tier=( 1 2 3 ) psa=( 0 1 ) ) level(84) noestimcheck
margins, at( tier=( 1 2 3 ) psa=( 0 1 ) ) level(95) noestimcheck

margins, at( tier=( 1 2 3 ) psa=( 0 (0.1) 1 ) ) level(84) noestimcheck
}

{Figure 4. Share of respondents who change their willingness to accept a decision after they learn that another government supports a decision.

by tier, sort : tabulate second_answer_original
}

{Figure 5. The impact of support provided by another tier of government on the willingness to accept a decision.

xtset id tier

*IMPORTANT NOTE: The point estimates are different from those produced by R and shown in Figure 5 in the main text. This is because Stata and R take different (respondent) base categories. The differences between the point estimates are the same.

*The point estimates are statistically significantly different from each other at p<0.05 when their 84% CIs do not overlap and at p<0.01 when their 95% CIs do not overlap; see data and methods. R and Stata produce slightly different CIs whereby estimates are different at the second (hundreths) or third (thousands) digit behind the decimal point. In some instances, this lead to some discrepancies between R and Stata in assigning statistical significance. In all cases of discrepancies,the R estimates are more conservative, i.e. R indicates non-significance and p<0.05 whereas Stata indicates respectively p<0.05 and p<0.01. The statistical significance levels shown in the Figures in the main text and in the Supplementary Materials are based on the more conservative R estimates. 

**#Figures 5A-C: Municipality decides to close kindergarten.
{
**IMPORTANT NOTE: Set the base categories for tier and treatment_nr to get estimates for the municipality taking a decision.

xtreg second_answer ib(3).tier i.first_answer##ib(3).treatment_nr##c.psa, fe cluster(id)

*Figure 5A: Municipality decides to close kindergarten and county supports.
{
margins, at( tier=3 first_answer=1 treatment_nr==1 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=2 treatment_nr==1 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=3 treatment_nr==1 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=4 treatment_nr==1 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=3 first_answer=1 treatment_nr==1 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=2 treatment_nr==1 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=3 treatment_nr==1 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=4 treatment_nr==1 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
*Figure 5B: Municipality decides to close kindergarten and national government supports.
{
margins, at( tier=3 first_answer=1 treatment_nr==6 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=2 treatment_nr==6 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=3 treatment_nr==6 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=4 treatment_nr==6 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=3 first_answer=1 treatment_nr==6 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=2 treatment_nr==6 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=3 treatment_nr==6 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=4 treatment_nr==6 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
*Figure 5C: Municipality decides to close kindergarten and county and national government support.
{
margins, at( tier=3 first_answer=1 treatment_nr==2 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=2 treatment_nr==2 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=3 treatment_nr==2 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=3 first_answer=4 treatment_nr==2 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=3 first_answer=1 treatment_nr==2 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=2 treatment_nr==2 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=3 treatment_nr==2 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=3 first_answer=4 treatment_nr==2 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
}
**#Figures 5D-F: County decides to close upper secondary school.
{
**IMPORTANT NOTE: Set the base categories for tier and treatment_nr to get estimates for the county taking a decision.

xtreg second_answer ib(2).tier i.first_answer##ib(1).treatment_nr##c.psa, fe cluster(id)

*Figure 5D: County decides to close upper secondary school and municipality supports.
{
margins, at( tier=2 first_answer=1 treatment_nr==3 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=2 treatment_nr==3 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=3 treatment_nr==3 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=4 treatment_nr==3 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=2 first_answer=1 treatment_nr==3 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=2 treatment_nr==3 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=3 treatment_nr==3 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=4 treatment_nr==3 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
*Figure 5E: County decides to close upper secondary school and national government supports.
{
margins, at( tier=2 first_answer=1 treatment_nr==6 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=2 treatment_nr==6 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=3 treatment_nr==6 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=4 treatment_nr==6 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=2 first_answer=1 treatment_nr==6 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=2 treatment_nr==6 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=3 treatment_nr==6 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=4 treatment_nr==6 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
*Figure 5F: County decides to close upper secondary school and municipality and national government support.
{
margins, at( tier=2 first_answer=1 treatment_nr==5 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=2 treatment_nr==5 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=3 treatment_nr==5 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=2 first_answer=4 treatment_nr==5 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=2 first_answer=1 treatment_nr==5 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=2 treatment_nr==5 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=3 treatment_nr==5 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=2 first_answer=4 treatment_nr==5 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
}
**#Figures 5G-I: National government decides to close a department of a university (college).
{
**IMPORTANT NOTE: Set the base categories for tier and treatment_nr to get estimates for the national government taking a decision.

xtreg second_answer ib(1).tier i.first_answer##ib(6).treatment_nr##c.psa, fe cluster(id)

*Figure 5G: National government decides to close a department of a university (college) and municipality supports.
{
margins, at( tier=1 first_answer=1 treatment_nr==3 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=2 treatment_nr==3 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=3 treatment_nr==3 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=4 treatment_nr==3 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=1 first_answer=1 treatment_nr==3 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=2 treatment_nr==3 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=3 treatment_nr==3 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=4 treatment_nr==3 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
*Figure 5H: National govenrment decides to close a department of a university (college) and county supports.
{
margins, at( tier=1 first_answer=1 treatment_nr==1 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=2 treatment_nr==1 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=3 treatment_nr==1 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=4 treatment_nr==1 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=1 first_answer=1 treatment_nr==1 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=2 treatment_nr==1 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=3 treatment_nr==1 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=4 treatment_nr==1 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
*Figure 5I: National govenrment decides to close a department of a university (college) and municipality and county supports.
{
margins, at( tier=1 first_answer=1 treatment_nr==4 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=2 treatment_nr==4 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=3 treatment_nr==4 psa=( 0.44 0.88 ) ) level(84) noestimcheck
margins, at( tier=1 first_answer=4 treatment_nr==4 psa=( 0.44 0.88 ) ) level(84) noestimcheck

margins, at( tier=1 first_answer=1 treatment_nr==4 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=2 treatment_nr==4 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=3 treatment_nr==4 psa=( 0.44 0.88 ) ) level(95) noestimcheck
margins, at( tier=1 first_answer=4 treatment_nr==4 psa=( 0.44 0.88 ) ) level(95) noestimcheck
}
}
